Diversity and space–time dynamics of the bacterial communities in cotton (<i>Gossypium hirsutum</i>) rhizosphere soil
Bibliographic record
Abstract
Rhizosphere bacteria are key determinants of plant health and productivity. In this study, we used PCR-based next-generation sequencing to reveal the diversity and community composition of bacteria in the cotton rhizosphere from samples collected in Xinjiang Province, China. We identified 125 bacterial classes within 49 phyla from these samples. Proteobacteria (33.07% of total sequences), Acidobacteria (19.88%), and Gemmatimonadetes (11.19%) dominated the bacterial community. Marked differences were evident in the α-diversity of rhizosphere bacteria during different cotton plant growth and development stages. The operational taxonomic unit (OTU) numbers were highest in seedling and bud stages and decreased at the flowering and fruit-boll-opening stages. Forty-three OTUs from the Proteobacteria were common to all four periods of cotton development. Proteobacteria were more abundant in the rhizospheres of cotton from southern Xinjiang than from northern Xinjiang, while the opposite trend was observed for Acidobacteria. Gemmatimonadetes frequency was broadly the same in both northern and southern Xinjiang. These results suggest that there is abundant diversity in the microbiota of cotton rhizosphere soil. Proteobacteria and Actinobacteria dominated this microbial niche and bacterial communities in the seedling, bud, flowering, and boll-opening stages appear to be more similar to one another than to communities at the other growth stages.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".